The present invention relates to a spatial light modulator used in optical information processing equipment, and to a neural network circuit which performs input/output operations resembling those of the nervous system for use in such applications as pattern recognition, associative memory, and parallel processing.
Spatial light modulators are an essential component in optical logic operations, optical neurocomputing, and other optical operations. Optically addressed-type spatial light modulators, in particular, differ from linear sequence driven electrically addressed-types, and can be used for parallel processing of two-dimensional information, thus leading to expected applications in high speed image processing, operations which can be very time-consuming on conventional computing devices. Optical writing-type spatial light modulators such as these feature a photoconductive layer combined with a component (hereinafter the modulation component) the light transmittance of which varies according to an electrical field applied thereto.
In FIG. 11, there is shown a spatial light modulator 1104 wherein a photoconductive layer 1102 having a reflection metal film 1101 and a liquid crystal layer 1103 are combined with each other (See Japanese patent laid-open publication SHO62-169120). The conventional device of this type utilizes the non-linear input to output characteristics (threshold characteristics) of the liquid crystal and, thereby, performs thresholding operation to light incident upon the photoconductive layer 1102 (See I. Shariv, and A. A. Friesem: Optics Letters Vol. 14(10), 1989, PP. 485 to 487).
Recent neurocomputers modelled on the nerve network of living organisms have attracted attention due to the ability, using these, to easily achieve associative linkage, fuzzy processing, and program-less functions, functions which are difficult to achieve with conventional von Neumann computers. The greater part of any neurocomputer today consists of a program running on a conventional von Neumann computer, but it is essential to construct a neurocomputer in hardware if a wide range of neurocomputer applications is to be developed.
One direction which can be taken in hardware is the optical neurocomputer, a device which uses light as the data medium. This is because the parallelism of light is suited to the operation of a neurocomputer which performs operations using the parallel dynamics of plural neurons. Light also enables high speed operation, and optical interconnection, which does not require hard wiring similar to electrical circuits for transmission, facilitates the implementation of multiple connections between neurons and thus simulates synapses. Light as a data medium thus offers many features which cannot be achieved with LSI and other devices which use electricity as the data medium. As a result, various optical neurocomputer designs have been proposed.
One operation which is basic to neurocomputing is to obtain the sum of plural input data entering the neuron, and to perform thresholding operation on the result. Building a spatial light modulator with this operating function is the single most important step in developing a neurocomputer in hardware.
However, there are no proposals in the prior art for a spatial light modulator with optical summation and optical thresholding operation or for an optical neurocomputer using such devices. In a conventional optical neural network system, the optical summation is done electrically using light collection by lenses or diffraction devices or a light detector array, and the thresholding operation of the optical neurocomputer uses an electronic circuit after photoelectric conversion by light receiving devices.
In the case of the conventional spatial light modulator 1104 shown by way of example in FIG. 11, it is impossible to perform exact optical summation for a plurality of light bundles incident to the reflection metal layer 1101 with a variety of light intensities, because the photoconductivity .sigma..sub.ph of the photoconductive layer 1102 is not proportional to the intensity of the incident light I.sub.ph. In other words, in an equation .sigma..sub.ph .varies.I.sub.ph.sup.a, the index "a" is quite different from 1.0. In such a case wherein the photoconductive layer does not satisfy the condition a=1.0, lenses and diffraction devices are used to collect a plurality of light bundles onto a point on the photoconductive layer in order to perform the optical summation. However, according to this method, it is difficult to miniaturize the system since distances are needed to be maintained between the photoconductive layer and lenses or diffraction devices. Further, it gives low yield, poor mass manufacturability and accordingly high costs due to reasons for necessity of taking alignment between the photoconductive layer and lenses or diffraction devices and fabricating various lenses and diffraction devices of micron order in an accurate manner.
Electronic circuits or computers have therefore been used for thresholding operation in conventional optical neurocomputers because of the lack of a spatial light modulator with optical summation and thresholding operation functions. Advanced intelligent data processing functions simulating human recognition and association have been reported to be based on the hierarchical structure of the neural network, but unless we have access to spatial light modulators capable of performing optical summation and optical thresholding operation operations, any hierarchical structure network will require an opto-electric conversion and electro-optical conversion each time thresholding operation is performed. This necessitates a complex electrical circuit, prevents full use of the parallel properties of light, and effectively lowers the operating speed.